###Sexual selection on a female copulatory device in an insect with nuptial gifts### #Behavioural Ecology and Sociobiology #Jessica H. Browne1,2 #Darryl T. Gwynne1 #1 Department of Ecology and Evolutionary Biology, University of Toronto Mississauga, Mississauga, Ontario L5L 1C6, Canada #2 E-mail: jbrowne@mta.ca, Current address: Department of Biology Mount Allison University, 62 York St. Sackville, NB, E4L 1E2, Canada library(readr) library(ggplot2) library(MASS) #residuals library(car) library(psych) library(permutes) library(buildmer) library(nlme) library(lmerTest) ####################################### **FEMALE BATEMAN GRADIENTS** ############################################ attach(bateman) View(bateman) str(bateman) bateman$year <-as.factor(bateman$year) bateman$site <-as.factor(bateman$site) bateman$mates <-as.numeric(mates) bateman$total.offspring <-as.numeric(total.offspring) bateman$mature.offspring <-as.numeric(mature.offspring) ###Create standardized variables## mn.size<-mean(size, na.rm=TRUE, data=bateman) bateman[,8] <-(bateman[,4]/mn.size) mn.mates<-mean(mates, na.rm=TRUE, data=bateman) bateman[,9] <-(bateman[,5]/mn.mates) mn.toffspring<-mean(total.offspring, na.rm=TRUE, data=bateman) bateman[,10] <-(bateman[,6]/mn.toffspring) mn.moffspring<-mean(mature.offspring, na.rm=TRUE, data=bateman) bateman[,11] <-(bateman[,7]/mn.moffspring) ########## USING TOTAL EGGS LAID ############ totbateman.lm <-lm(total.offspring~ mates, data=bateman) #raw gradient summary(totbateman.lm) S.totbateman.lm <- lm(R.totoffspring ~ R.mates, data = bateman) #standardized gradient summary(S.totbateman.lm) totbateman.perms <- perm.glmer(R.totoffspring~ R.mates, data=bateman, nperm=5000, type='regression') #permutation for p values totbateman.perms plot(mates, total.offspring) #visualize trend abline(lm(total.offspring~mates)) #test assumptions plot(totbateman.lm) shapiro.test(resid(totbateman.lm)) #normality of residuals hist(resid(totbateman.lm)) ############ USING DEVELOPED EGGS ############ matbateman.lm <-lm(mature.offspring~ mates, data=bateman) #raw gradient summary(matbateman.lm) S.matbateman.lm <- lm(R.matoffspring ~ R.mates + year, data = bateman) #standardized gradient summary(S.matbateman.lm) matbateman.perms <- perm.lm(R.matoffspring~ R.mates, data=bateman, nperm=5000, type='regression') #permutation for p values matbateman.perms plot(mates, mature.offspring) #visualize trend abline(lm(mature.offspring~mates)) #assumptions plot(matbateman.lm) shapiro.test(resid(matbateman.lm)) #normality of residuals hist(resid(matbateman.lm)) ################# EFFECTS OF BODY SIZE ################## ### BODY SIZE ALONE ### sizetot.lm <- lm(R.totoffspring~ R.size + R.mates, data=bateman) #eggs laid summary(sizetot.lm) sizetot.perms <- perm.lm(R.totoffspring~ R.size + R.mates, data=bateman[complete.cases(bateman[,c("R.size")]),], nperm=5000, type='regression') #permutation for p values sizetot.perms sizemat.lm <- lm(R.matoffspring~ R.size + R.mates, data=bateman) #eggs developed summary(sizemat.lm) sizemat.perms <- perm.lm(R.matoffspring~ R.size +R.mates, data=bateman[complete.cases(bateman[,c("R.size")]),], nperm=5000, type='regression') #permutation for p values sizemat.perms ### SIZE INCLUDED IN BATEMAN MODEL ### size.totbateman.lm <- lm(R.totoffspring~ R.size + R.mates, data=bateman) #total eggs laid summary(size.totbateman.lm) size.totbateman.perms <- perm.lm(R.totoffspring~ R.size + R.mates, data=bateman[complete.cases(bateman[,c("R.size")]),], nperm=5000, type='regression') #permutation for p values size.totbateman.perms size.matbateman.lm <- lm(R.matoffspring~ R.size + R.mates, data=bateman) #eggs developed summary(size.matbateman.lm) size.matbateman.perms <- perm.lm(R.matoffspring~ R.size + R.mates, data=bateman[complete.cases(bateman[,c("R.size")]),], nperm=5000, type='regression') #permutation for p values size.matbateman.perms ##################### INTERACTIONS WITH SITE AND YEAR ##################### #Visualize ggplot() + geom_smooth(data = d, aes(x=mates,y=total.offspring), method=lm, size=1.5, se=TRUE, level=0.95, color=1, fill="grey80", fullrange=T) + geom_point(data = d, aes(x = mates, y = total.offspring), shape= "circle", color=1, size=1.5, position= position_jitter(width=0.4, height=0)) + #POINT DETAILS geom_smooth(data = d, aes(x=mates, y=total.offspring, linetype= site, color= site), method=lm, size=0.75, se=F, level=F, fullrange=T) + geom_smooth(data = d, aes(x=mates,y=total.offspring, linetype=year, color = year), method=lm, size=0.75, se=F, level=F, fullrange=T) ggplot() + geom_smooth(data = d, aes(x=mates,y=mature.offspring), method=lm, size=1.5, se=TRUE, level=0.95, color=1, fill="grey80", fullrange=T) + geom_point(data = d, aes(x = mates, y = mature.offspring), shape= "circle", color=1, size=1.5, position= position_jitter(width=0.4, height=0)) + #POINT DETAILS geom_smooth(data = d, aes(x=mates, y=mature.offspring, linetype= site, color= site), method=lm, size=0.75, se=F, level=F, fullrange=T) + geom_smooth(data = d, aes(x=mates,y=mature.offspring, linetype=year, color = year), method=lm, size=0.75, se=F, level=F, fullrange=T) ##TEST SITE INTERACTIONS site.totbateman.lm <-lm(R.totoffspring~ R.mates +site*R.mates, data=bateman) #total eggs laid summary(site.totbateman.lm) site.matbateman.lm <-lm(R.matoffspring~ R.mates +site*R.mates, data=bateman) #developed eggs summary(site.matbateman.lm) ##TEST YEAR INTERACTIONS year.totbateman.lm <-lm(R.totoffspring~ R.mates + year*R.mates, data=bateman) #eggs laid summary(year.totbateman.lm) year.matbateman.lm <-lm(R.matoffspring~ R.mates +year*R.mates, data=bateman) #developed eggs summary(year.matbateman.lm) #### BATEMAN GRADIENTS SEPARATED BY YEAR #### ##2002 - restandardize variables attach(bateman02) mn.size<-mean(size, na.rm=TRUE, data=bateman02) bateman02[,8]<-(bateman02[,4]/mn.size) mn.mates<-mean(mates, na.rm=TRUE, data=bateman02) bateman02[,9]<-(bateman02[,5]/mn.mates) mn.toffspring<-mean(total.offspring, na.rm=TRUE, data=bateman02) bateman02[,10] <-(bateman02[,6]/mn.toffspring) mn.moffspring<-mean(mature.offspring, na.rm=TRUE, data=bateman02) bateman02[,11] <-(bateman02[,7]/mn.moffspring) ##Total Offspring 2002 tot.lm02 <- lm(total.offspring ~ mates, data=bateman02) #Raw 2002 summary(tot.lm02) tot.lm02 <- lm(R.totoffspring ~ R.mates, data=bateman02) #Standardized 2002 summary(tot.lm02) tot.perms02<- perm.lm(R.totoffspring~ R.mates, data=bateman02, nperm=5000, type='regression') #permutation for p values tot.perms02 #Developed offspring 2002 *ESM ONLY mat.lm02 <- lm(mature.offspring ~ mates, data=bateman02) #Raw 2002 summary(mat.lm02) mat.lm02 <- lm(R.matoffspring ~ R.mates, data=bateman02) #Standardized 2002 summary(mat.lm02) mat.perms02 <- perm.lm(R.matoffspring~ R.mates, data=bateman02, nperm=5000, type='regression') #permutation for p values mat.perms02 #test assumptions plot(tot.lm02) shapiro.test(resid(tot.lm02)) #normality of residuals hist(resid(tot.lm02)) plot(mat.lm02) shapiro.test(resid(mat.lm02)) #normality of residuals hist(resid(mat.lm02)) ###2017 - restandardize variables attach(bateman17) mn.size<-mean(size, na.rm=TRUE, data=bateman17) bateman17[,8]<-(bateman17[,4]/mn.size) mn.mates<-mean(mates, na.rm=TRUE, data=bateman17) bateman17[,9]<-(bateman17[,5]/mn.mates) mn.toffspring<-mean(total.offspring, na.rm=TRUE, data=bateman17) bateman17[,10] <-(bateman17[,6]/mn.toffspring) mn.moffspring<-mean(mature.offspring, na.rm=TRUE, data=bateman17) bateman17[,11] <-(bateman17[,7]/mn.moffspring) #Total offspring 2017 tot.lm17 <- lm(total.offspring ~ mates, data=bateman17) #Raw 2017 summary(tot.lm17) tot.lm17 <- lm(R.totoffspring ~ R.mates, data=bateman17) #Standardized 2017 summary(tot.lm17) tot.perms17<- perm.lm(R.totoffspring~ R.mates, data=bateman17, nperm=5000, type='regression') #permutation for p values tot.perms17 #Developed offspring 2017 *ESM ONLY mat.lm17 <- lm(mature.offspring ~ mates, data=bateman17) #Raw 2017 summary(mat.lm17) mat.lm17 <- lm(R.matoffspring ~ R.mates, data=bateman17) #Standardized 2017 summary(mat.lm17) mat.perms17 <- perm.lm(R.matoffspring~ R.mates, data=bateman17, nperm=5000, type='regression') #permutation for p values mat.perms17 #test assumptions plot(tot.lm17) shapiro.test(resid(tot.lm17)) #normality of residuals hist(resid(tot.lm17)) plot(mat.lm17) shapiro.test(resid(mat.lm17)) #normality of residuals hist(resid(mat.lm17)) #### BATEMAN GRADIENTS SEPARATED BY SITE *ESM ONLY #### #Kiri - restandardize variables attach(batemanK) mn.size<-mean(size, na.rm=TRUE, data=batemanK) batemanK[,8]<-(batemanK[,4]/mn.size) mn.mates<-mean(mates, na.rm=TRUE, data=batemanK) batemanK[,9]<-(batemanK[,5]/mn.mates) mn.toffspring<-mean(total.offspring, na.rm=TRUE, data=batemanK) batemanK[,10] <-(batemanK[,6]/mn.toffspring) mn.moffspring<-mean(mature.offspring, na.rm=TRUE, data=batemanK) batemanK[,11] <-(batemanK[,7]/mn.moffspring) Kiri.tot.lm <- lm(total.offspring ~ mates, data=batemanK) #Raw Kiriwhakapapa total eggs laid summary(Kiri.tot.lm) Kiri.tot.lm <- lm(R.totoffspring ~ R.mates, data=batemanK) #Standardized Kiriwhakapapa total eggs laid summary(Kiri.tot.lm) Kiri.tot.perms<- perm.lm(R.totoffspring~ R.mates, data=batemanK, nperm=5000, type='regression') #permutation for p values Kiri.tot.perms Kiri.mat.lm <- lm(mature.offspring ~ mates, data=batemanK) #Raw Kiriwhakapapa developed eggs summary(Kiri.mat.lm) Kiri.mat.lm <- lm(R.matoffspring ~ R.mates, data=batemanK) #Standardized Kiriwhakapapa developed eggs summary(Kiri.mat.lm) Kiri.mat.perms<- perm.lm(R.matoffspring~ R.mates, data=batemanK, nperm=5000, type='regression') #permutation for p values Kiri.mat.perms #test assumptions plot(Kiri.tot.lm) shapiro.test(resid(Kiri.tot.lm)) #normality of residuals hist(resid(Kiri.tot.lm)) plot(Kiri.mat.lm) shapiro.test(resid(Kiri.mat.lm)) #normality of residuals hist(resid(Kiri.mat.lm)) #Pamly - restandardize variables # attach(batemanPN) mn.size<-mean(size, na.rm=TRUE, data=batemanPN) batemanPN[,8]<-(batemanPN[,4]/mn.size) mn.mates<-mean(mates, na.rm=TRUE, data=batemanPN) batemanPN[,9]<-(batemanPN[,5]/mn.mates) mn.toffspring<-mean(total.offspring, na.rm=TRUE, data=batemanPN) batemanPN[,10] <-(batemanPN[,6]/mn.toffspring) mn.moffspring<-mean(mature.offspring, na.rm=TRUE, data=batemanPN) batemanPN[,11] <-(batemanPN[,7]/mn.moffspring) PN.tot.lm <- lm(total.offspring ~ mates, data=batemanPN) #Raw Palmy eggs laid summary(PN.tot.lm) PN.tot.lm <- lm(R.totoffspring ~ R.mates, data=batemanPN) #Standardized Palmy eggs laid summary(PN.tot.lm) PN.tot.perms<- perm.lm(R.totoffspring~ R.mates, data=batemanPN, nperm=5000, type='regression') #permutation for p values PN.tot.perms PN.mat.lm <- lm(mature.offspring ~ mates, data=batemanPN) #Raw Palmy developed eggs summary(PN.mat.lm) PN.mat.lm <- lm(R.matoffspring ~ R.mates, data=batemanPN) #Standardized Palmy developed eggs summary(PN.mat.lm) PN.mat.perms<- perm.lm(R.matoffspring~ R.mates, data=batemanPN, nperm=5000, type='regression') #permutation for p values PN.mat.perms #test assumptions plot(PN.tot.lm) shapiro.test(resid(PN.tot.lm)) #normality of residuals hist(resid(PN.tot.lm)) plot(PN.mat.lm) shapiro.test(resid(PN.mat.lm)) #normality of residuals hist(resid(PN.mat.lm)) ########################BATEMAN FIGURE INCLUDED IN PUBLICATION############################ bateman$year <-as.factor(bateman$year) d<-bateman my_font='Arial' #Total eggs P1 <- ggplot() + geom_smooth(data = d, aes(x=mates,y=total.offspring), method=lm, size=1.5, se=TRUE, level=0.95, color=1, fill="grey80", fullrange=T) + geom_point(data = d, aes(x = mates, y = total.offspring), shape= "circle", color=1, size=1.5, position= position_jitter(width=0.4, height=0)) + #POINT DETAILS geom_smooth(data = d, aes(x=mates, y=total.offspring, linetype= site, color= site), method=lm, size=0.75, se=F, level=F, fullrange=T) + geom_smooth(data = d, aes(x=mates,y=total.offspring, linetype=year, color = year), method=lm, size=0.75, se=F, level=F, fullrange=T) + geom_text(data=d, x=0.1, y=80, label= "A", size=6, family=my_font) + scale_color_manual(values=c("grey70", "grey40", "grey70", "grey40")) + scale_linetype_manual(values = c("longdash", "longdash", "twodash", "twodash")) + labs(y="Number of eggs laid", x="") + #AXIS LABELS scale_x_continuous(limits=c(0,8), breaks=seq(0,8, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(0,80), breaks=seq(0,80, by=10)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.position = "none" ) plot(P1) ##Developed Eggs P2<- ggplot() + geom_smooth(data = d, aes(x=mates,y=mature.offspring), method=lm, size=1.5, se=TRUE, level=0.95, color=1, fill="grey80", fullrange=T) + geom_point(data = d, aes(x = mates, y = mature.offspring), shape= "circle", colour =1, size=1.5, position= position_jitter(width=0.4, height=0)) + #POINT DETAILS geom_smooth(data = d, aes(x=mates,y=mature.offspring, linetype=site, color=site), method=lm, size=0.75, se=F, level=F, fullrange=T) + geom_smooth(data = d, aes(x=mates,y=mature.offspring, linetype=year, color=year), method=lm, size=0.75, se=F, level=F, fullrange=T) + geom_text(data=d, x=0.1, y=60, label= "B", size=6, family=my_font) + scale_color_manual(values=c("grey70", "grey40", "grey70", "grey40"), name = "Collections", labels = c("2002", "2017", "Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("longdash", "longdash", "twodash", "twodash"), name = "Collections", labels = c("2002", "2017", "Kiriwhakapapa", "Palmerston North")) + labs(y="Number of developed eggs", x="") + #AXIS LABELS scale_x_continuous(limits=c(0,8), breaks=seq(0,8, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(0,60), breaks=seq(0,60, by=10)) + theme_bw()+ #background theme(legend.text = element_text(size=12, family=my_font), legend.title = element_text(size=14, family=my_font), axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), ) plot(P2) ## COMBINE FIGURES ## install.packages("devtools") devtools::install_github("thomasp85/patchwork") library(patchwork) P1+P2 ##############################**SEXUAL SELECTION ON ACCESSORY ORGANS**############################## library(readr) library(MASS) #residuals library(car) library(ggplot2) library(fields) library(psych) attach(females.ss) str(females.ss) females.ss$year = as.factor(females.ss$year) females.ss$site <-as.factor(site) females.ss$mates <-as.numeric(mates) ###STANDARDIZE VARIABLES## females.ss$body.size <- scale(females.ss$body.size) females.ss$AO.length <- scale(females.ss$AO.length) females.ss$AO.width <- scale(females.ss$AO.width) mn.mates<-mean(mates, na.rm=TRUE, data=females.ss) females.ss[,7]<-(females.ss[,7] / mn.mates) mneggs<-mean(eggs, na.rm=TRUE, data=female.ss) females.ss[,8]<-(females.ss[,8]/mneggs) ####RUN MODEL#### females.lm <- lm(mates ~ AO.length + AO.width + body.size, data= females.ss) summary(females.lm) females.perms <- perm.lm(mates ~ AO.length + AO.width + body.size, data= females.ss, nperm=5000, type='regression') #permutation for p values females.perms #include year as random effect *SINGULAR FIT; NOT ENOUGH POWER mates.lm <- lmer(mates ~ AO.length + AO.width + body.size +(1|year), data=females.ss) summary(mates.lm) mates.perms.R <- perm.lmer(mates ~ AO.length + AO.width + body.size +(1|year), data= females.ss, nperm=5000, type='regression') #permutation for p values mates.perms.R ###Check Assumptions plot(females.lm) shapiro.test(resid(females.lm)) #normality of residuals hist(resid(females.lm)) ######VISUALIZE VARITATION BETWEEN SITES AND YEARS###### ggplot(data=females.ss, aes(x= body.size, y = mates, color=site)) + geom_point() + geom_smooth(method = lm) #test further ggplot(data=females.ss, aes(x= AO.length, y = mates, color=site)) + geom_point() + geom_smooth(method = lm) #no issue ggplot(data=females.ss, aes(x= AO.width, y = mates, color=site)) + geom_point() + geom_smooth(method = lm) #test further ggplot(data=females.ss, aes(x= body.size, y = mates, color=year)) + geom_point() + geom_smooth(method = lm) ggplot(data=females.ss, aes(x= AO.length, y = mates, color=year)) + geom_point() + geom_smooth(method = lm) ggplot(data=females.ss, aes(x= AO.width, y = mates, color=year)) + geom_point() + geom_smooth(method = lm) ####TEST INTERACTIONS WITH SITE#### interaction.lm1 <- lm(mates ~ body.size + body.size*site, data= females.ss) summary(interaction.lm1) interaction.lm3 <- lm(mates ~ AO.width+ AO.width*site, data= females.ss) summary(interaction.lm3) interaction.lm2 <- lm(mates ~ AO.length+ AO.length*site, data= females.ss) summary(interaction.lm2) ######## VARIATION ACROSS SITES *PLOTS INCLUDED IN ESM####### #SITE #body size PA <- ggplot() + geom_point(data=females.ss, aes(x= body.size, y = mates, color=site, shape=site)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= body.size, y = mates, color=site, linetype=site), method=lm, se=T, fill="grey70") + geom_smooth(data=females.ss, aes(x= body.size, y = mates), method=lm, color=1, se=F) + scale_color_manual(values=c("lightcoral", "royalblue3"), name = "Collections", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("dotdash", "dotdash"), name = "Collections", labels = c("Kiriwhakapapa", "Palmerston North")) + labs(y="Relative number of mates", x="Body size") + #AXIS LABELS scale_x_continuous(limits=c(-2.5,3), breaks=seq(-2.5,3, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.75,3), breaks=seq(-0.75,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.position = "none" ) plot(PA) #Organ width PB <- ggplot() + geom_point(data=females.ss, aes(x= AO.width, y = mates, color=site, shape=site)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= AO.width, y = mates, color=site, linetype=site), method=lm, se=T, fill="grey70") + geom_smooth(data=females.ss, aes(x= AO.width, y = mates), method=lm, color=1, se=F) + scale_color_manual(values=c("lightcoral", "royalblue3"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("dotdash", "dotdash"), name = "Collections Site", labels = c("Kiriwhakapapa", "Palmerston North")) + labs(y="", x="Accesory organ width") + #AXIS LABELS scale_x_continuous(limits=c(-2,2.5), breaks=seq(-2,2.5, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.5,3), breaks=seq(-0.5,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.position = "none" ) plot(PB) #organ length PC <- ggplot() + geom_point(data=females.ss, aes(x= AO.length, y = mates, color=site, shape=site)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= AO.length, y = mates, color=site, linetype=site), method=lm, se=TRUE, fill="grey70") + geom_smooth(data=females.ss, aes(x= AO.length, y = mates), method=lm, color=1, se=F) + guides(color=guide_legend(override.aes=list(fill=NA)))+ scale_shape_manual(values=c("circle", "triangle"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_color_manual(values=c("lightcoral", "royalblue3"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("dotdash", "dotdash"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + labs(y="", x="Accesory organ length") + #AXIS LABELS scale_x_continuous(limits=c(-2,3), breaks=seq(-2,2.5, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.5,3), breaks=seq(-0.5,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.key.size = unit(1, 'cm'), legend.text = element_text(size=10) ) plot(PC) PA + PB + PC #########################**RELATIONSHIP WITH NUMBER OF EGSS** ################################## Eggs.lm <- lm(eggs ~ AO.length + AO.width + body.size, data=females.ss) #does AO size correlate with fecundity? summary(Eggs.lm) Eggs.perms <- perm.lm(eggs ~ AO.length + AO.width + body.size, data= females.ss, nperm=5000, type='regression') #permutation for p values Eggs.perms #include year as random effects Eggs.lm <- lmer(eggs ~ AO.length + AO.width + body.size +(1|year), data=females.ss) #does AO size correlate with fecundity? summary(Eggs.lm) Eggs.perms.R <- perm.lmer(eggs ~ AO.length + AO.width + body.size +(1|year), data= females.ss, nperm=5000, type='regression') #permutation for p values Eggs.perms.R plot(Eggs.lm) #####VISUALIZE VARIATION ACROSS SITES AND YEARS #### ggplot(data=females.ss, aes(x= body.size, y = eggs, color=site)) + geom_point() + geom_smooth(method = lm) #test further ggplot(data=females.ss, aes(x= AO.length, y = eggs, color=site)) + geom_point() + geom_smooth(method = lm) #no issue ggplot(data=females.ss, aes(x= AO.width, y = eggs, color=site)) + geom_point() + geom_smooth(method = lm) #test further ggplot(data=females.ss, aes(x= body.size, y = eggs, color=year)) + geom_point() + geom_smooth(method = lm) ggplot(data=females.ss, aes(x= AO.length, y = eggs, color=year)) + geom_point() + geom_smooth(method = lm) ggplot(data=females.ss, aes(x= AO.width, y = eggs, color=year)) + geom_point() + geom_smooth(method = lm) #####TEST INTERACTIONS WITH SITE###### interaction.lm1 <- lm(eggs ~ body.size+ body.size*site, data= females.ss) summary(interaction.lm1) interaction.lm3 <- lm(eggs ~ AO.width+ AO.width*site, data= females.ss) summary(interaction.lm3) interaction.lm2 <- lm(eggs ~ AO.length+ AO.length*site, data= females.ss) summary(interaction.lm2) ########VARIATION ACROSS SITES *PLOTS INCLUDED IN ESM####### PD <- ggplot() + geom_point(data=females.ss, aes(x= body.size, y = eggs, color=site, shape=site)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= body.size, y = eggs, color=site, linetype=site), method=lm, se=T, fill="grey80") + geom_smooth(data=females.ss, aes(x= body.size, y = eggs), method=lm, color=1, se=F) + scale_color_manual(values=c("lightcoral", "royalblue3"), name = "Collections", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("dotdash", "dotdash"), name = "Collections", labels = c("Kiriwhakapapa", "Palmerston North")) + labs(y="Relative number of eggs in abdomen", x="Body size") + #AXIS LABELS scale_x_continuous(limits=c(-2.5,3), breaks=seq(-2.5,3, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.5,3), breaks=seq(-0.5,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.position = "none" ) plot(PD) PE <- ggplot() + geom_point(data=females.ss, aes(x= AO.width, y = eggs, color=site, shape=site)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= AO.width, y = eggs, color=site, linetype=site), method=lm, se=T, fill="grey80") + geom_smooth(data=females.ss, aes(x= AO.width, y = eggs), method=lm, color=1, se=F) + scale_color_manual(values=c("lightcoral", "royalblue3"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("dotdash", "dotdash"), name = "Collections Site", labels = c("Kiriwhakapapa", "Palmerston North")) + labs(y="", x="Accesory organ width") + #AXIS LABELS scale_x_continuous(limits=c(-2,2.5), breaks=seq(-2,2.5, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.5,3), breaks=seq(-0.5,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.position = "none" ) plot(PE) PF <- ggplot() + geom_point(data=females.ss, aes(x= AO.length, y = eggs, color=site, shape=site)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= AO.length, y = eggs, color=site, linetype=site), method=lm, se=TRUE, fill="grey80") + geom_smooth(data=females.ss, aes(x= AO.length, y = eggs), method=lm, color=1, se=F) + guides(color=guide_legend(override.aes=list(fill=NA)))+ scale_shape_manual(values=c("circle", "triangle"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_color_manual(values=c("lightcoral", "royalblue3"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + scale_linetype_manual(values = c("dotdash", "dotdash"), name = "Collection Site", labels = c("Kiriwhakapapa", "Palmerston North")) + labs(y="", x="Accesory organ length") + #AXIS LABELS scale_x_continuous(limits=c(-2,3.5), breaks=seq(-2,3.5, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.5,3), breaks=seq(-0.5,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.key.size = unit(1, 'cm'), legend.text = element_text(size=10) ) plot(PF) PD + PE + PF ########VARIATION ACROSS YEARS *PLOT INCLUDED IN ESM####### Plot.year <- ggplot() + geom_point(data=females.ss, aes(x= AO.width, y = eggs, color=year, shape= year)) + #POINT DETAILS geom_smooth(data=females.ss, aes(x= AO.width, y = eggs, color=year, linetype=year), method=lm, se=TRUE, fill="grey80") + geom_smooth(data=females.ss, aes(x= AO.width, y = eggs), method=lm, color=1, se=F) + guides(color=guide_legend(override.aes=list(fill=NA)))+ scale_shape_manual(values=c("circle", "triangle", "square", "diamond"), name = "Collection Year", labels = c("2012", "2016", "2017", "2019")) + scale_color_manual(values=c("royalblue3", "lightcoral","darkorchid4", "cyan2"), name = "Collection Year", labels = c("2012", "2016", "2017", "2019")) + scale_linetype_manual(values = c("dashed", "dashed", "longdash", "longdash"), name = "Collection Year", labels = c("2012", "2016", "2017", "2019")) + labs(y="Relative number of eggs in the abdomen", x="Accesory organ width") + #AXIS LABELS scale_x_continuous(limits=c(-2,3), breaks=seq(-2,2.5, by=1)) + # LIMITS & INTERVALS scale_y_continuous(limits=c(-0.5,3), breaks=seq(-0.5,3, by=0.5)) + theme_bw()+ #background theme(axis.line = element_line(),panel.grid.minor=element_blank(), panel.grid.major.y = element_blank(), panel.grid.major.x = element_blank(), axis.text.x=element_text(size=12, color= "black", family=my_font), axis.title.x=element_text(size=12, family=my_font,vjust=0.01), axis.text.y=element_text(size=12, color= "black", family=my_font), axis.title.y=element_text(size=12, family=my_font,vjust=3), legend.key.size = unit(1, 'cm'), legend.text = element_text(size=10) ) plot(Plot.year)